Closed rashidakanchwala closed 3 days ago
@merelcht , @noklam , @astrojuanlu FYI.
Benefits:
- Utilising widely-used experiment tracking services would provide better features.
- Users will gain enhanced capabilities to store, visualise, and compare experiments.
- The decoupling of experiment tracking from Kedro's internal sessions and data versioning will allow us to evolve these features on Kedro Framework
My main question will be, what is the benefit of using kedro-viz instead of use mlflow for experiment tracking directly? Is the main value about providing an alternative UI for these toolings?
A couple of quick thoughts:
What would #2079 involve? Just separating the dependencies or also removing stuff from the UI? Do we have any sort of estimation of that work? I'm just wondering if it's worth the effort. Do we have any evidence that people don't use Viz because this feature exists, or that people find Viz is "too large" because of experiment tracking? Otherwise there won't be much user gain by just making it optional compared to having it there by default.
(Continuing that conversation there)
My main question will be, what is the benefit of using kedro-viz instead of use mlflow for experiment tracking directly? Is the main value about providing an alternative UI for these toolings?
@noklam great question, I'm making two assumptions that we should evaluate:
Before embarking on this task, we should probably do some research (or look up what has been said) about current pain points with MLflow, and specifically its UI
For sure, I will add that as well to the ticket.
Added this point
After weighing pros and cons, we decided against this. We're removing the feature instead.
Description
Kedro-Viz currently supports experiment tracking through the Kedro's MetricsDataset or JSONDataset and it also uses Kedro sessions. However, with this we offer limited functionality to the user and this could possible be made better by replacing the backend to connect to more specialised/mainstream experiment tracking services such as MLFLow, W&B
The frontend for experiment tracking in Kedro-Viz is already in place, so the goal is to retain this while modifying the backend to fetch data from APIs of popular experiment tracking services.
Proposed Change:
Benefits:
Possible work:
Next Steps:
Checklist